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Record W2806377820 · doi:10.1213/ane.0000000000003508

Fibrinogen Concentrate in Cardiovascular Surgery: A Meta-analysis of Randomized Controlled Trials

2018· review· en· W2806377820 on OpenAlexaff
Jingyi Li, Junsong Gong, Fang Zhu, Jessica Moodie, Amy Newitt, Lavanya Uruthiramoorthy, Davy Cheng, Janet Martin

Bibliographic record

VenueAnesthesia & Analgesia · 2018
Typereview
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsImpactWestern University
Fundersnot available
KeywordsMedicinePerioperativeFibrinogenMeta-analysisPlaceboRandomized controlled trialConfidence intervalRelative riskSurgeryInternal medicineCochrane LibraryBlood transfusionPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Postoperative bleeding remains a frequent complication after cardiovascular surgery and may contribute to serious morbidity and mortality. Observational studies have suggested a relationship between low endogenous plasma fibrinogen concentration and increased risk of postoperative blood loss in cardiac surgery. Although the transfusion of fibrinogen concentrate has been increasing, potential benefits and risks associated with perioperative fibrinogen supplementation in cardiovascular surgery are not fully understood. METHODS: PubMed, Cochrane Library, Ovid MEDLINE, Embase, Web of Science, and China National Knowledge Infrastructure were searched on January 15, 2017, with automated updates searched until February 15, 2018, to identify all randomized controlled trials (RCTs) of fibrinogen concentrate, whether for prophylaxis or treatment of bleeding, in adults undergoing cardiovascular surgery. All RCTs comparing fibrinogen infusion versus any other comparator (placebo/standard of care or another active comparator) in adult cardiovascular surgery and reporting at least 1 predefined clinical outcome were included. The random-effects model was used to calculate risk ratios and weighted mean differences (95% confidence interval [CI]) for dichotomous and continuous variables, respectively. Subgroup analyses by fibrinogen dose and by baseline risk for bleeding were preplanned. RESULTS: A total of 8 RCTs of fibrinogen concentrate in adults (n = 597) of mixed risk or high risk undergoing cardiovascular surgery were included. Compared to placebo or inactive control, perioperative fibrinogen concentrate did not significantly impact risk of all-cause mortality (risk ratio, 0.41; 95% CI, 0.12-1.38; I = 10%; P = .15). Fibrinogen significantly reduced incidence of allogeneic red blood cell transfusion (risk ratio, 0.64; 95% CI, 0.49-0.83; I = 0%; P = .001). No significant differences were found for other clinical outcomes. Subgroup analyses were unremarkable when analyzed according to fibrinogen dose, time of infusion initiation, mean cardiopulmonary bypass time, and rotational thromboelastometry/fibrinogen temogram use (all P values for subgroup interaction were nonsignificant). CONCLUSIONS: Current evidence remains insufficient to support or refute routine perioperative administration of fibrinogen concentrate in patients undergoing cardiovascular surgery. Fibrinogen concentrate may reduce the need for additional allogeneic blood product transfusion in cardiovascular surgery patients at high risk or with evidence of bleeding. However, no definitive advantage was found for reduction in risk of mortality or other clinically relevant outcomes. The small number of clinical events within existing randomized trials suggests that further well-designed studies of adequate power and duration to measure all-cause mortality, stroke, myocardial infarction, reoperation, and thromboembolic events should be conducted. Future studies should also address cost-effectiveness relative to standard of care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.332
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.1140.113
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.156
GPT teacher head0.359
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations61
Published2018
Admission routes1
Has abstractyes

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